Operating Range Scheduled Robust Dahlin Algorithm to Typical Industrial Process with Input Constraint

Abstract

There is a class of typical nonlinear industrial process, which can be characterized by a first-order inertia plus pure delay model in an operating range, but the model parameters are different in different operating ranges. Usually, a set of Proportion Integration Differentiation (PID) controllers may be used to control the process, and the controllers have different parameters in different operating areas. However, the adjustment process of the PID controllers’ parameters is not an easy job in practice, and the control performance may also be not perfect. The Dahlin algorithm may provide very good control performance for the process, but its control performance may become very poor if the model parameters are not accurate and/or the input is constrained. Faced with this issue, this paper proposes an Operating-Range Scheduled Robust Dahlin Algorithm (ORSRDA) for the process control with input constraint, which is designed on the basis of a nominal first-order inertia plus pure delay model and the given parameters uncertainty. The process operating ranges are divided into pre-designed several zones according to the difference between output setting value and current output when a new setting appears. For each operating range, the parameters of ORSRDA are obtained by solving a min-max problem offline to guarantee the closed-loop system’s robust stability and acquire the best step-response control performance. To eliminate the steady state error, the integration control action is added into the ORSRDA when the system output is close to its setting value. The proposed method is applied to temperature control of an experimental electric furnace to demonstrate its effectiveness and implement procedure.